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Strong employer brand, metro location, and mid-level SRE role increase applicant competition.
Core SRE skills transfer across industries, but Azure and data-engineering focus increases domain specificity.
Explicit 6-8 year requirement and extensive mandatory tech stack make shortlisting stringent.
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Own reliability, scalability, and performance of high-availability systems for large-scale Data Engineering projects.
Develop and manage continuous monitoring, automated deployments, and active alerting for infrastructure using Cloud native tools and IaC frameworks.
Handle system outages with root cause analysis, performance tuning, and enforcement of security policies aligned with organizational standards.
6-8 years of hands-on experience in maintaining large-scale, high-availability Data Engineering solutions and services.
Proficiency with Azure cloud platform, Azure DevOps, and Azure PaaS components.
Experience with Kubernetes administration and tools including Terraform, ARM, YAML, Docker, Helm, Argo, Istio, and Grafana.
Master's or Bachelor's degree in Computer Science, Information Science, or equivalent engineering discipline.
Experienced with cloud native, containerized environments and CI/CD frameworks focused on Azure ecosystem.
Familiar with implementing and measuring Service Level Objectives (SLOs) and Service Level Indicators (SLIs) for sophisticated service architectures.
Skilled at automating infrastructure as code, monitoring large scale systems, and applying DevSecOps security best practices in Kubernetes environments.